Automatic Correction of Syntax Errors in SuperSQL Queries

Shunsuke Otawa, Kento Goto, Motomichi Toyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

SuperSQL is an extended language of SQL. By structuring the output of relational databases, SuperSQL enables the user to generate various types of structured documents with various layouts which are not represented in SQL. There is a problem that the larger and more complicated the SuperSQL query is, the more difficult it is to detect errors and the more time is spent on debugging. In this study, we propose a system that automatically detects and corrects syntax errors in user queries. When a query parsing fails, the system reanalyzes the query and predicts a correction by using deep learning. To modify the query, we use recurrent neural network and attention mechanism. By presenting the predicted modifications to users, the burden of debugging can be reduced and the efficiency of user's work can be improved.

Original languageEnglish
Title of host publication22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Proceedings
EditorsMaria Indrawan-Santiago, Eric Pardede, Ivan Luiz Salvadori, Matthias Steinbauer, Ismail Khalil, Gabriele Kotsis
PublisherAssociation for Computing Machinery
Pages28-33
Number of pages6
ISBN (Electronic)9781450389228
DOIs
Publication statusPublished - 2020 Nov 30
Event22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020 - Virtual, Online, Thailand
Duration: 2020 Nov 302020 Dec 2

Publication series

NameACM International Conference Proceeding Series

Conference

Conference22nd International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2020
CountryThailand
CityVirtual, Online
Period20/11/3020/12/2

Keywords

  • Automatic Error Correction
  • Deep Learning
  • SuperSQL

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

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